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Volcanic islands are exciting real-world climate and landscape laboratories. When geologically young (<10Ma) they provide a simplified and spatially limited setting for testing landscape evolution
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datasets with phylogenies and environmental variables, the project aims to rapidly explore trait evolution, predict dispersal potential, and assess climate-related risks. This work bridges biodiversity
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, providing vital insights for managing water, land, and communities in a warming world. Working with leading scientists at Loughborough University, the University of Southampton, and Colorado State University
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to determine what type of heat therapy protocols are well tolerated and can be well integrated into people’s life. Therefore, this programme of study aims to develop practical and feasible heat therapy protocols
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, sediment transport, and flood risk, delivering evidence to guide sustainable river management and climate resilience. Based at Loughborough University with collaboration from Newcastle University, you’ll be
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. Analysis of images will investigate the efficacy of manual digital approaches (e.g., Dot Dot Goose) and the development of a marine litter characterisation and quantification algorithm for automated analysis
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This project aims to bring together evidence from climate projections, risk assessment and observations to develop and evaluate event-based storylines based on recent flooding in Leicestershire, UK
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Science), a global leader in marine science, the project will develop scalable, low-cost embedded vision systems to analyze marine biodiversity and detect anthropogenic debris. The core challenge is
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. Development of novel processing techniques Modelling techniques that can inform the direction of experimental activity Physical, mechanical and materials characterisation techniques Data-driven approaches
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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven